Re: Confusion Matrix in Weka Experiments

Dear Peter, 

thank you very much. I guess my previous mail did not go via outlook. I am new in programming especially in Java. Therefore I found python weka wrapper easier for me. However, is there a way to compare datasets rather than classifiers. I have like 3 classifiers and 3 databases (my code is below). 

Also is there a way to implement (ClassifierSplitEvaluator.setPredTargetColumn(boolean)) in python wrapper ? 


    exp = SimpleCrossValidationExperiment(
            classification=True,
            runs=10,
            folds=10,
            datasets=datasets,
            classifiers=classifiers,
            result=result)
    exp.setup()
    exp.run()

    loader = weka.core.converters.loader_for_file(result)

    data = loader.load_file(result)

    matrix = ResultMatrix(classname="weka.experiment.ResultMatrixPlainText")
    tester = Tester(classname="weka.experiment.PairedCorrectedTTester")
    tester.resultmatrix = matrix


    comparison_col = data.attribute_by_name("Percent_correct").index

    tester.instances = data


    print(tester.header(comparison_col))
    print(tester.multi_resultset_full(0, comparison_col))
    print(tester.multi_resultset_full(1, comparison_col))
    print(tester.multi_resultset_full(2, comparison_col))
    # plot
    plot_exp.plot_experiment(matrix, title="Cross-Validation", measure="Percent_correct", wait=True)


Best regards,

Cem
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